Creating LLM Judges to Measure Domain-Specific Agent Quality

Learn to develop specialized evaluation frameworks for measuring the effectiveness of domain-specific AI agents in this 34-minute conference talk from Databricks. Explore methodologies that go beyond standard LLM benchmarks to assess agent quality across specialized knowledge domains, tailored workflows, and task-specific objectives. Discover practical approaches for designing robust LLM judges that align with business goals and provide meaningful insights into agent capabilities and limitations. Master tools for creating domain-relevant evaluation datasets and benchmarks that accurately reflect real-world use cases, understand approaches for developing LLM judges to measure domain-specific metrics, and implement strategies for interpreting results to drive iterative improvement in agent performance. Transform your domain-specific agents from experimental tools to trusted enterprise solutions with measurable business value through proper evaluation methodologies presented by Nikhil Thorat and Samraj Moorjani, Software Engineers at Databricks.